References
- Ahmed, M. A., & Alkhamis, T. M. (2009). Simulation optimization for an emergency department healthcare unit in kuwait. European Journal of Operational Research, 198(3), 936–942. https://doi.org/https://doi.org/10.1016/j.ejor.2008.10.025
- Ashburn, M. A., & Staats, P. S. (1999). Management of chronic pain. The Lancet, 353(9167), 1865–1869. https://doi.org/https://doi.org/10.1016/S0140-6736(99)04088-X
- Aston, G. (2014). Hospitals & health networks. Retrieved July 10, 2016, from http://www.hhnmag.com/articles/3989-awareness-of-patient-safety-grows-with-increased-outpatient-surgeries/.
- Baesler, F. F., & Sepúlveda, J. A. (2001). Multi-objective simulation optimization for a cancer treatment center. In Simulation Conference, 2001. Proceedings of the Winter (Vol. 2, pp. 1405–1411). IEEE.
- Center for Disease Control and Prevention. (2010). National Center for Health Statistics. Retrieved July 10, 2016, from http://www.cdc.gov/nchs/fastats/inpatient-surgery.htm/.
- Center for Disease Control and Prevention. (2016). Wide-ranging online data for epidemiologic research (wonder). National Center for Health Statistics.
- Cetin, E., & Sarul, L. S. (2009). A blood bank location model: A multiobjective approach. European Journal of Pure and Applied Mathematics, 2(1), 112–124.
- Chen, V. C., Ruppert, D., & Shoemaker, C. A. (1999). Applying experimental design and regression splines to high-dimensional continuous-state stochastic dynamic programming. Operations Research, 47(1), 38–53. https://doi.org/https://doi.org/10.1287/opre.47.1.38
- Chevlen, E. (2004). Optimizing the use of opioids in the elderly population. American Journal of Pain Management, 14(2 SUPP), 19S–24S.
- Cooner, E., & Amorosi, S. (1997). The study of pain and older americans. Louis Harris and Associates.
- Czyzyk, J., Mesnier, M. P., & Moré, J. J. (1998). The neos server. IEEE Computational Science and Engineering, 5(3), 68–75. https://doi.org/https://doi.org/10.1109/99.714603
- Dolan, E. D. (2001). The NEOS Server 4.0 Administrative Guide. (Technical Memorandum No. ANL/MCS-TM-250). Mathematics and Computer Science Division, Argonne National Laboratory.
- European Medical Tourist. (2016). European Medical Tourist Oswestry Disability Index. Retrieved February 16, 2016, from http://www.europeanmedicaltourist.com/88/.
- Federal Interagency Forum on Aging-Related Statistics. (2008). Older Americans 2008: Key indicators of well-being. Government Printing Office.
- Fine, P. (2004). Difficulties and challenges in the treatment of chronic pain in the older adult. American Journal of Pain Management, 14(2 SUPP), 2S–8S.
- Gatchel, R. J. (2016). Personal communication.
- Gould, B. E., & Dyer, R. (2010). Pathophysiology for the health professions-e-book. Elsevier Health Sciences.
- Gropp, W., & Moré, J. J. (1997). Optimization environments and the neos server. In M. D. Buhman & A. Iserles (Eds.), Approximation theory and optimization (pp. 167–182). Cambridge University Press.
- Gu, W., Wang, X., & McGregor, S. E. (2010). Optimization of preventive health care facility locations. International Journal of Health Geographics, 9(1), 17. https://doi.org/https://doi.org/10.1186/1476-072X-9-17
- LeBoulluec, A., Ohol, N., Chen, V., Zeng, L., Rosenberger, J., & Gatchel, R. (2018). Handling time-varying confounding in state transition models for dynamic optimization of adaptive interdisciplinary pain management. IISE Transactions on Healthcare Systems Engineering, 8(1), 83–92. https://doi.org/https://doi.org/10.1080/24725579.2017.1418770
- Lin, C.-F., LeBoulluec, A. K., Zeng, L., Chen, V. C., & Gatchel, R. J. (2014). A decision-making framework for adaptive pain management. Health Care Management Science, 17(3), 270–283. https://doi.org/https://doi.org/10.1007/s10729-013-9252-0
- Lipson, S. J. (2004). Spinal-fusion surgery - advances and concerns. The New England Journal of Medicine, 350(7), 643–644. https://doi.org/https://doi.org/10.1056/NEJMp038162
- Mak, W.-K., Morton, D. P., & Wood, R. K. (1999). Monte carlo bounding techniques for determining solution quality in stochastic programs. Operations Research Letters, 24(1-2), 47–56. https://doi.org/https://doi.org/10.1016/S0167-6377(98)00054-6
- McGann, K. (2007). Fundamental aspects of pain assessment and management. Quay Books division.
- Murphy, S. A. (2005). An experimental design for the development of adaptive treatment strategies. Statistics in Medicine, 24(10), 1455–1481. https://doi.org/https://doi.org/10.1002/sim.2022
- National Institute of Health. (2020). Opioid overdose crisis. Retrieved June 24, 2020, fromvhttps://www.drugabuse.gov/drug-topics/opioids/opioid-overdose-crisis.
- National VA Pain Outcomes Working Group. (2003). Vha pain outcomes toolkit.
- Nolte, E., Knai, C., & McKee, M. (2008). Managing chronic conditions: experience in eight countries. (No. 15). WHO Regional Office Europe.
- Ohol, N. (2018). Adjusting for time varying confounding in adaptive interdisciplinary pain management program [Unpublished doctoral dissertation]. Faculty of the Graduate School, University of Texas at Arlington.
- Rawat, R., & Manry, M. T. (2017). Second order training of a smoothed piecewise linear network. Neural Processing Letters, 46(3), 915–942.
- Silverstein, J. H., McLeskey, C. H., Reves, J., & Rooke, G. A. (2008). Geriatric anesthesiology. Springer.
- Verweij, B., Ahmed, S., Kleywegt, A. J., Nemhauser, G., & Shapiro, A. (2003). The sample average approximation method applied to stochastic routing problems: a computational study. Computational Optimization and Applications, 24(2), 289–333.
- Wang, N., Rosenberger, J., Iqbal, G. M. D., Chen, V., Gatchel, R. J., Noe, C., & LeBoulluec, A. K. (2019). Two-stage stochastic programming for interdisciplinary pain management. IISE Transactions on Healthcare Systems Engineering, 9(2), 131–145. https://doi.org/https://doi.org/10.1080/24725579.2019.1610528
- Wilson, N., Kariisa, M., Seth, P., Smith, H., & Davis, N. L. (2020). Drug and opioid-involved overdose deaths–united states, 2017–2018. MMWR. Morbidity and Mortality Weekly Report, 69(11), 290–297. https://doi.org/https://doi.org/10.15585/mmwr.mm6911a4
- Zhang, W., Cao, K., Liu, S., & Huang, B. (2016). A multi-objective optimization approach for health-care facility location-allocation problems in highly developed cities such as hong kong. Computers, Environment and Urban Systems, 59, 220–230. https://doi.org/https://doi.org/10.1016/j.compenvurbsys.2016.07.001